Coseismic Ionospheric Disturbances Research Articles

A New Analytical Simulation Code of Acoustic-Gravity Waves of Seismic Origin and Rapid Co-Seismic Thermospheric Disturbance Energetics

A New Analytical Simulation Code of Acoustic-Gravity Waves of Seismic Origin and Rapid Co-Seismic Thermospheric Disturbance Energetics

Co-seismic ionospheric disturbances due to 2004 Sumatra-Andaman earthquake

The Coseismic Ionospheric Disturbances (CID) due to the 26th December 2004 earthquake of Mw 9.2, which occurred in the Sumatra-Andaman subduction zone, are analyzed using cGPS-aided Total Electron Content (TEC) measurements. For the CID analysis, data from nearby seven Sumatran GPS Array (SuGAr) and two International GNSS Stations (IGS) located to the south of the epicenter, at a distance of 500–1000km (near-field) and two IGS stations located to the north-west of the epicenter at a distance of 2000km (far-field) are considered. The CIDs with a propagation velocity of 595–694m/s arrived within 2–10min after the earthquake, depending upon the distance of a station from the epicentre. Variations in the CIDs can be prominently seen at the nearest cGPS Station SAMP immediately after the earthquake. NTUS, being the farthest station shows some small variations. The delay in the occurrence of variations at GPS sites can also be associated with rupture propagation. Because all the stations used in our analysis are located south of the epicenter and rupture of the earthquake propagated in the north, the trend of rupture propagation could not be analyzed clearly.

Co-seismic ionospheric disturbances characteristics in different azimuths following the 2022 Mexico earthquake from GNSS observations

Co-seismic ionospheric disturbances characteristics in different azimuths following the 2022 Mexico earthquake from GNSS observations

The 6 February 2023 Türkiye Earthquake Sequence as Detected in the Ionosphere

AbstractOn 6 February 2023, a series of large earthquakes struck Turkey and Northern Syria. The main earthquake of Mw 7.8 occurred at 01:17:34 UTC and was followed by the three notable (Mw > 5.5) aftershocks within the next 18 min. Then, ∼9 hr later, the biggest aftershock with magnitude Mw 7.5 and a Mw 6.0 earthquake occurred to the north‐east from the first main earthquake. In this work, we use data of ground‐based Global Navigation Satellite Systems (GNSS) receivers in Turkey, Israel and Cyprus to analyze the ionospheric response to this series of earthquakes. We separate these events in two groups: the first sequence of earthquakes (at 01–02 UTC) and the second sequence (at 10–11 UTC). For the first sequence, we observe a clear N‐shaped total electron content (TEC) response after the Mw 7.8 mainshock earthquake and Mw 6.7 aftershock, and a smaller TEC disturbance that is, most likely, caused by the Mw 5.6 earthquake. The latter is now the smallest earthquake detected by using ionospheric GNSS data. The co‐seismic ionospheric disturbances (CSID) propagated from the epicentral area in the south‐west direction with velocities of about 750–830 m/s. For the second sequence, we observed the response to the Mw 7.5 aftershock earthquake and the Mw 6.0 aftershock. The CSID propagated both to the south‐west and the north‐west to the epicentral area, with velocities of about 950–1,100 m/s.

Study on co-seismic ionospheric disturbance of Alaska earthquake on July 29, 2021 based on GPS TEC

With the rapid development of space geodetic information technology, the Global Positioning System (GPS) has been widely used in seismology and space environmental research. Typically, the occurrence of a large earthquake will lead to some changes in the ionosphere, this phenomenon is called coseismic ionospheric disturbances (CIDs). In this contribution, differential slant total electron content (dSTEC) is used to study the anomalous characteristics of the ionosphere. First, based on the ionospheric dSTEC time series and two-dimensional disturbance detection, the temporal and spatial characteristics of ionospheric disturbances can be accurately analysed. Secondly, using wavelet transform spectrum analysis and disturbance propagation velocity, it can be determined that the disturbance sources of this earthquake can be identified as acoustic wave, gravity wave and Rayleigh wave. Finally, in order to further clarify the direction of the earthquake disturbance, this study focuses on proposing an innovative method for the disturbance propagation direction, and determines that there are two directions of the propagation of the CIDs of the Alaski earthquake.

Ionospheric Response to the 6 February 2023 Turkey–Syria Earthquake

Two strong earthquakes occurred in Turkey on 6 February 2023, at 01:17:34 (nighttime, Mw = 7.8) and at 10:24:50 UT (daytime, Mw = 7.5). The seismo-ionospheric impact is an important part of the near-Earth environment state. This paper provides the first results on the ionospheric effects associated with the aforementioned earthquakes. We used data from global navigation satellite system (GNSS) receivers and ionosondes. We found that both earthquakes generated circle disturbance in the ionosphere, detected by GNSS data. The amplitude of the ionospheric response caused by daytime M7.5 earthquake exceeded by five times that caused by nighttime M7.8 earthquake: 0.5 TECU/min and 0.1 TECU/min, respectively, according to the ROTI data. The velocities of the earthquake-related ionospheric waves were ~2000 m/s, as measured by ROTI, for the M7.5 earthquake. TEC variations with 2–10 min periods showed velocities from 1500 to 900 m/s as disturbances evolved. Ionospheric disturbances occurred around epicenters and propagated to the south by means of 2–10 min TEC variations. ROTI data showed a more symmetric distribution with irregularities observed both to the South and to the North from 10:24:50 UT epicenter. The ionospheric effects were recorded over 750 km from the epicenters. Ionosonde located 420/490 km from the epicenters did not catch ionospheric effects. The results show significant asymmetry in the propagation of coseismic ionospheric disturbances. We observed coseismic ionospheric disturbances associated with Rayleigh mode and acoustic modes, but we did not observe disturbances associated with acoustic gravity mode.

Slow Fault Slip Signatures in Coseismic Ionospheric Disturbances

AbstractRise times of earthquake moment release influence the spectra of seismic waves. For example, slow fault movements in tsunami earthquakes excite larger tsunamis than expected from intensities of short‐period seismic waves. Here we compare amplitudes of two different atmospheric waves, long‐period internal gravity waves and short‐period acoustic waves, excited by coseismic vertical crustal movements. We observe them as coseismic ionospheric disturbances by measuring ionospheric electrons using global navigation satellite systems. Four regular megathrust earthquakes Mw 8.0–9.0 showed that the internal gravity waves become ten times stronger as the magnitude increases by one. We found that the 2010 Mentawai earthquake, a typical tsunami earthquake, excited internal gravity waves stronger than those expected by this empirical relationship. On the other hand, amplitudes of acoustic waves excited by tsunami earthquakes were normal. This suggests that slow fault ruptures excite long‐period atmospheric waves efficiently, leaving a slow earthquake signature in ionospheric disturbances.

Lithosphere Ionosphere Coupling Associated with Seismic Swarm in the Balkan Peninsula from ROB-TEC and GPS

With the rapid development of global navigation satellite systems (GNSS) and their increasingly wide range of applications in atmospheric science, total electron content (TEC) data are widely used in the theoretical study of layer coupling related to seismicity. This study detected and analyzed pre-earthquake ionospheric anomalies (PEIA) by using TEC data from the Royal Observatory of Belgium (ROB), and analyzed coseismic ionospheric disturbance (CID) with vertical TEC (VTEC) from the GPS stations in earthquake preparation areas. The results show that PEIA appear to increase continuously from 08:00–12:00 UT in the 3 days before a seismic swarm of Mw > 5.0. The ionosphere over the seismogenic zones exhibited large-scale anomalies when multiple seismogenic zones of the Balkan Peninsula spatially and temporally overlapped. Moreover, the TEC around the earthquake centers showed a positive anomaly lasting for 7 h. In a single seismogenic zone in Greece, the TEC around the earthquake center reached over +3.42 TECu. In addition, the CID observed from GPS stations shows that with the increase in the number of earthquakes, the ionosphere over the seismogenic area is more obviously disturbed, and after three strong earthquakes, TEC suddenly decreased over the seismogenic area and formed a phenomenon similar to an ionospheric hole. We conclude that a lithosphere–atmosphere–ionosphere coupling mechanism existed before the seismic swarm appeared in the Balkan Peninsula. Earthquake-induced VTEC anomalies occurred more frequently within a 3–10 day window before the earthquake. This phenomenon is particularly evident when multiple seismogenic zones overlap spatiotemporally.

Directivity of Coseismic Ionospheric Disturbances Propagation Following the 2016 West Sumatra Earthquake Using Three-Dimensional Tomography GNSS-TEC

Ionospheric disturbances caused by the 2016 West Sumatra earthquake have been studied using total electron content (TEC) measurements by Global Navigation Satellite System (GNSS) observation stations evenly distributed in Sumatra and Java, Indonesia. Previous observation focused on the coseismic ionospheric disturbances (CID) detected 11–16 min after the earthquake. The maximum TEC amplitude measured was 2.9 TECU (TEC Unit) with speed between 1 and 1.72 km/s. A comprehensive analysis needs to be done to see how the growth and direction of the movement of the CID due to the earthquake is using the 3D tomography method. The dimensions of 3D tomographic model are setup to 1° × 1.2° × 75 km. The continuity constraints were used to stabilize the solution, and multiple resolution tests with synthetic data were conducted to evaluate the precision of the results. This research focuses on the anomalous movement of the ionosphere observed in three dimensions. From the model, the positive anomaly initially appeared 11 min after the earthquake at the altitude of 300 km, which is the highest ionization layer and correspond to the electron density profile using IRI model. The anomalous movement appeared 12 min after the mainshock and moved 1° toward the geomagnetic field every minute. The density anomaly of the ionosphere began to weaken 8 min after the appearance of CID. To check the accuracy of the 3D tomography model, we carried out two types of tests, namely checkerboard resolution test and the second resolution test.

Three-Dimensional Tomography of Coseismic Ionospheric Disturbances Following the 2018 Palu Earthquake and Tsunami from GNSS Measurements

Preliminary research analyzed the Coseismic Ionospheric Disturbances (CIDs) of the strike-slip earthquake that occurred in Palu on September 28, 2018 (Mw = 7.5) and the materialization of a TEC anomaly with an amplitude of 0.4 TECU approximately 10–15 min later. The TEC anomaly amplitude is also affected by the magnitude of the earthquake moment; therefore, 3D analysis is needed to determine the spatial distribution of the ionospheric disturbances. This research aims to analyze the ionospheric disturbance of an earthquake in 3D using the Global Navigation Satellite System (GNSS) from the Geospatial Information Agency (BIG) or InaCORS stations spread over Sulawesi, Kalimantan, West Nusa Tenggara, East Nusa Tenggara, Bali, and Java with a 30 s sampling interval using GLONASS and GPS satellites. The checkerboard accuracy test was also carried out to evaluate the reliability of the 3D tomography model. The result showed that CIDs occur to the north and south of the epicenter around the equator, following the N-S Asymmetry theory. Furthermore, the tomography results indicate the presence of dominant and positive anomaly values at an altitude of 300–500 km. This follows the characteristics of variations in the ionosphere layer, where an altitude of 300–500 km is included in the F layer. The dominant anomaly at an altitude of 300 km is in accordance with the theory of the ionosphere’s height, which experiences maximum ionization at an altitude of ∼300 km (F layer) by Chapman’s profile. We also conducted preseismic studies of ionospheric anomalies before the earthquake as an additional analysis.

Near-real-time detection of co-seismic ionospheric disturbances using machine learning

SUMMARY Tsunamis generated by large earthquake-induced displacements of the ocean floor can lead to tragic consequences for coastal communities. Measurements of co-seismic ionospheric disturbances (CIDs) offer a unique solution to characterize an earthquake’s tsunami potential in near-real-time (NRT) since CIDs can be detected within 15 min of a seismic event. However, the detection of CIDs relies on human experts, which currently prevents the deployment of ionospheric methods in NRT. To address this critical lack of automatic procedure, we designed a machine-learning-based framework to (1) classify ionospheric waveforms into CIDs and noise, (2) pick CID arrival times and (3) associate arrivals across a satellite network in NRT. Machine-learning models (random forests) trained over an extensive ionospheric waveform data set show excellent classification and arrival-time picking performances compared to existing detection procedures, which paves the way for the NRT imaging of surface displacements from the ionosphere.

Rapid Tsunami Potential Assessment Using GNSS Ionospheric Disturbance: Implications from Three Megathrusts

The current tsunami early warning systems always issue alarms once large undersea earthquakes are detected, inevitably resulting in false warnings since there are no deterministic scaling relations between earthquake size and tsunami potential. In this paper, we assess tsunami potential by analyzing co-seismic ionospheric disturbances (CIDs). We examined CIDs of three megathrusts (the 2014 Mw 8.2 Iquique, the 2015 Mw 8.3 Illapel, and the recent 2021 Mw 8.2 Alaska events) as detected by Global Navigation Satellite System (GNSS) observations. We found that CIDs near the epicenter generated by the 2021 Mw 8.2 Alaska event were significantly weaker than those of the two Chilean events, despite having similar earthquake magnitudes. The propagation direction of CIDs from the Mw 8.2 Alaska earthquake further revealed ruptures toward the deeper seismogenic zone, implying less seafloor uplift and hazardous flooding. Our work sheds light on incorporating GNSS-based CIDs for more trustworthy tsunami warning systems.

The First Evidence for the Detection of CIDs Masked by Equatorial Plasma Bubbles From GPS‐TEC Data

AbstractThe strong influence of equatorial plasma bubbles (EPBs) appears to mask co‐seismic ionospheric disturbances (CIDs) for the earthquakes occurring in the equatorial low‐latitudes during the post‐sunset time. Based on GPS‐TEC data, we attempted to unveil the CIDs for the two great seismic events that are the 2005 M 8.6 Nias and 2017 M 8.2 Mexico earthquakes. In the case of the Nias earthquake, the CIDs have been identified in the bandpass filtered vertical total electron content data obtained from selective GPS satellite‐receiver pairs. For the Mexico earthquake, the EPB anomalies are dominant, making the appearance of CIDs hazy. However, the N‐shaped vertical total electron content anomalies masked by the plasma bubble anomalies in the bandpass filtered data are clear after applying the frequency domain singular spectrum analysis (SSA). Furthermore, the frequency domain SSA indicates the acoustic and surface waves of CIDs for both earthquakes. It also shows the signature of propagating gravity waves for the Mexico earthquake that has generated a moderate tsunami. Thus, the present study illustrates that the CIDs concealed by the non‐stationary EPB anomalies for earthquakes occurring in low latitude equatorial regions during post‐sunset become visible.

Co-Seismic Ionospheric Disturbances Following the 2016 West Sumatra and 2018 Palu Earthquakes from GPS and GLONASS Measurements

The study of ionospheric disturbances associated with the two large strike-slip earthquakes in Indonesia was investigated, which are West Sumatra on 2 March 2016 (Mw = 7.8), and Palu on 28 September 2018 (Mw = 7.5). The anomalies were observed by measuring co-seismic ionospheric disturbances (CIDs) using the Global Navigation Satellite System (GNSS). The results show positive and negative CIDs polarization changes for the 2016 West Sumatra earthquake, depending on the position of the satellite line-of-sight, while the 2018 Palu earthquake shows negative changes only due to differences in co-seismic vertical crustal displacement. The 2016 West Sumatra earthquake caused uplift and subsidence, while the 2018 Palu earthquake was dominated by subsidence. TEC anomalies occurred about 10 to 15 min after the two earthquakes with amplitude of 2.9 TECU and 0.4 TECU, respectively. The TEC anomaly amplitude was also affected by the magnitude of the earthquake moment. The disturbance signal propagated with a velocity of ~1–1.72 km s−1 for the 2016 West Sumatra earthquake and ~0.97–1.08 km s−1 for the 2018 Palu mainshock earthquake, which are consistent with acoustic waves. The wave also caused an oscillation signal of ∼4 mHz, and their azimuthal asymmetry of propagation confirmed the phenomena in the Southern Hemisphere. The CID signal could be identified at a distance of around 400–1500 km from the epicenter in the southwestern direction.

Ionospheric Disturbances Observed Following the Ridgecrest Earthquake of 4 July 2019 in California, USA

Earthquakes are known to generate disturbances in the ionosphere. Such disturbances, referred to as co-seismic ionospheric disturbances, or ionoquakes, were previously reported for large earthquakes with magnitudes Mw≥ 6.6. This paper reports ionoquakes associated with the Ridgecrest earthquakes of magnitude (Mw=6.4), that occurred on 4 July 2019 in California, USA. The ionoquakes manifested in total electron content (TEC) in the form of traveling ionospheric disturbances (TIDs) within 1 h from the mainshock onset. These seismic-origin TIDs have unique wave characteristics that distinguish them from TIDs of non-seismic origin arising from a moderate geomagnetic activity on the same day. Moreover, in the space-time domain of the detection of seismic-origin TIDs, TIDs are absent on the day before and day after the earthquake day. Their spectral characteristics relate them to the Earth’s normal modes and atmospheric resonance modes. We found the ground velocity associated with the mainshock, rather than the ground displacement, satisfies the threshold criteria for detectable ionoquakes in TEC measurements. Numerical simulation suggested that the coupled seismo–atmosphere–ionosphere (SAI) dynamics energized by the atmospheric waves are responsible for the generation of ionoquakes. This study’s findings demonstrate the potential of using TEC measurement to detect the ionospheric counterparts of moderate earthquakes.

Three-dimensional Tomography of Coseismic Ionospheric Disturbances from the 2016 West Sumatera Earthquake

Global Navigation Satellite System (GNSS) is a navigation system that uses satellite signals to determine its position, which consists of several satellites arranged in a constellation system. GNSS transmits signals to receivers on Earth. The GNSS receiver determines the user’s position, speed, and time by processing the signals transmitted by the satellites. The initial purpose of launching the GNSS was for navigation purposes, but along with its development, GNSS can be used for the purposes of observing deformation of the earth’s crust and in studying the atmosphere. The delayed wave data when passing through the ionosphere can be used to obtain Total Electron Content (TEC) values which then used to study ionospheric disturbances. Ionospheric disturbances are caused by various phenomena, the most common one is the ionospheric disturbances caused by the induction of acoustic and gravitational waves excited by co seismic crustal motions from large earthquakes. Ionospheric disturbances that happened before an earthquake are called Pre-seismic Ionospheric Disturbances and those that occur after an earthquake are called Co-seismic Ionospheric Disturbances (CID). Most studies of ionospheric disturbances still provide information on the timing and value of TEC anomalies in 2D form. Therefore, in this study, a 3D ionosphere profile modelling using computed 3D tomography will be carried out. The 3D information provided is in the form of time, ionosphere altitude and TEC anomaly value by utilizing GNSS data. The TEC anomaly value is obtained from the calculation of linear combination of the ionosphere. This study aims to obtain a spatial and temporal analysis of the CID caused by the West Sumatra Earthquake on March 2, 2016.

Locating surface deformation induced by earthquakes using GPS, GLONASS and Galileo ionospheric sounding from a single station

Monitoring earthquakes to rapidly forecast their consequences remains a challenging task, especially in areas far from seismic and geodetic networks. Large and shallow earthquakes induce disturbances in the ionospheric Total Electron Content (TEC). These disturbances are commonly detected using Global Navigation Satellite Systems (GNSS) stations that can sound the ionosphere at great distances. To address this instrumentation sparsity issue, we assess a single GNSS station's ability to constrain the origin location of a coseismic ionospheric disturbance (CID) using observations of TEC. We develop a grid-search method that explores different trial origins (i.e. source locations) to determine which synthetic CID signal best matches the observed TEC time series. We confirm that a larger number of monitoring satellites enhances the opportunity to have the favorable geometrical coverage of satellites needed to resolve CID origins. We use TEC data acquired during two earthquakes having different moment magnitudes: a Mw 7.1 from Turkey and a Mw 7.8 from New Zealand. Using a well-placed multi-GNSS station we are able to retrieve the CID origin with an accuracy of 50 km and a theoretical precision of the same order. We conclude that a very sparse network of multi-GNSS stations can provide an independent estimate of the spatial distribution of large scale coseismic motions, including offshore areas 200–300 km from the coastline.

Vertical Propagation of Coseismic Ionospheric Disturbances Associated With the Foreshock of the Tohoku Earthquake Observed Using HF Doppler Sounding

AbstractThe vertical propagation of coseismic ionospheric disturbances (CIDs) associated with the foreshock of the Tohoku earthquake was examined using an HF Doppler sounding system. The sounding system used in this study received radio waves at four different frequencies (5.006, 6.055, 8.006, and 9.595 MHz), indicating that ionospheric disturbances can be observed at up to four altitudes. CIDs were observed at these four frequencies in association with the foreshock of the Tohoku earthquake. From the propagation speed of the coseismic disturbances, it is assumed that the ground motion caused by the Rayleigh wave propagating from the epicenter generates the acoustic mode wave propagating upward, causing the neutral atmospheric particles to move vertically. To examine the characteristics of the acoustic wave, we determined the ratio of the vertical speed of the neutral particles to that of the ground motion observed by a seismometer. The vertical profiles of the ratio are roughly explained in terms of the characteristics of the acoustic mode wave resulting from the ground motion. However, the absolute values of the ratio are smaller than the theoretical ratio estimated by the atmospheric mass density and the attenuation model considering the viscosity, thermal conductivity, and relaxation losses. This result implies that the CIDs in this event may be affected by the nonlinear behavior of the acoustic mode wave.

Onset Altitudes of Co‐Seismic Ionospheric Disturbances Determined by Multiple Distributions of GNSS TEC After the Foreshock of the 2011 Tohoku Earthquake on March 9, 2011

AbstractWe investigate ionospheric disturbances using the total electron content (TEC) data obtained from the radio signals emitted from three satellites after the foreshock of the 2011 Tohoku Earthquake on March 9, 2011. Co‐seismic ionospheric disturbances (CIDs) appeared to extend from an onset point concentrically in all of the satellite data. We have found, however, that the geographic coordinates of the onset points did not coincide if the observed CIDs were assumed to occur at one altitude. Admitting that the altitudes of the onset points are different, we searched for coinciding geographic coordinates of the onset points by changing the altitudes and identified the altitude of the three onset points to be 107.8, 131.8, and 133.3 km and the onset time at these altitudes. As a result, the vertical velocity of an acoustic‐gravity wave is estimated to be 448 m/s from the travel time between the altitudes of 107.8 and 131.8 km and 370 m/s between the altitude of 107.8 and 133.3 km. This is comparable to the speed of sound calculated using the empirical model NRLMSISE‐00. The present study provides a method of determining the altitude and geographic coordinates of the onset point from the ionospheric TEC analysis independently of the seismic data. Furthermore, the source location of the acoustic‐gravity wave is simultaneously determined because its wavefront propagating vertically arrives earliest at an altitude that TEC disturbance is detectable.

Relating Far‐Field Coseismic Ionospheric Disturbances to Geological Structures

AbstractClear near‐epicentral coseismic ionospheric disturbances (CIDs) are observed following the Gorkha and May 2015 Nepal earthquakes and only the Gorkha earthquake excited observable far‐field CIDs up to 3,000 km from the epicenter. The near‐epicentral CIDs exhibit concentric fields to the south and north of the epicenter. A north‐south asymmetry of the CIDs is clearly observed in the near‐epicentral area of both earthquakes. The velocity and period of the main part of the near‐epicentral CIDs are ∼1,000 m/s and ∼6 min, respectively. The wavefronts of the far‐field CIDs related to the Gorkha earthquake are mostly straight lines that completely differ from the near‐epicentral CIDs. The horizontal trace of the far‐field CIDs reaches velocities of ∼2.5 km/s based on their distance from the epicenter and the CID arrival time. After identifying the propagation direction of the far‐field CIDs on a series of two‐dimensional (2D) total electron content (TEC) maps, we obtain the real horizontal velocity of far‐field CIDs, which is ∼1.0 km/s, and the period is ∼3 min, which corresponds to that of acoustic waves in the ionosphere. We find a discontinuity of the far‐field CIDs around the Sichuan Basin, which suggests that deep sedimentation can reduce seismic energy coupling into the atmosphere and then the ionosphere. In addition, by introducing a simple acoustic source into the SAMI2 simulation, we show that the large electron density of the background ionosphere and steep inclination of the geomagnetic field are favorable conditions for the generation of detectable CIDs.